Forecasting Foreign Exchange Rate Movements With K Nearest Neighbour Ridge Regression And Feed Forward Neural Networks
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Forecasting Foreign Exchange Rate Movements With K Nearest Neighbour Ridge Regression And Feed Forward Neural Networks
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Author : Milan Fičura
language : en
Publisher:
Release Date : 2017
Forecasting Foreign Exchange Rate Movements With K Nearest Neighbour Ridge Regression And Feed Forward Neural Networks written by Milan Fičura and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Three different classes o ...
Forecasting Foreign Exchange Rate Movements With K Nearest Neighbor Ridge Regression And Feed Forward Neural Networks
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Author : Milan Fičura
language : en
Publisher:
Release Date : 2019
Forecasting Foreign Exchange Rate Movements With K Nearest Neighbor Ridge Regression And Feed Forward Neural Networks written by Milan Fičura and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Foreign Exchange Rate Forecasting With Artificial Neural Networks
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Author : Lean Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-26
Foreign Exchange Rate Forecasting With Artificial Neural Networks written by Lean Yu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-26 with Business & Economics categories.
This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges.
Forecasting Exchange Rates Using General Regression Neural Networks
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Author : Mark T. Leung
language : en
Publisher:
Release Date : 2004
Forecasting Exchange Rates Using General Regression Neural Networks written by Mark T. Leung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
In this study, we examine the forecastability of a specific neural network architecture called General Regression Neural Network (GRNN) and compare its performance with a variety of forecasting techniques, including Multi-Layered Feedforward Network (MLFN), multivariate transfer function, and random walk models. The comparison with MLFN provides a measure of GRNN's performance relative to the more conventional type of neural networks while the comparison with transfer function models examines the difference in predictive strength between the non-parametric and parametric techniques. The random walk model is used for benchmark comparison. Our findings show that GRNN not only has a higher degree of forecasting accuracy but also performs statistically better than other evaluated models for different currencies.
Forecasting Exchange Rates Using General Regression Neural Networks
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Author : Mark T. Leung
language : en
Publisher:
Release Date : 2006
Forecasting Exchange Rates Using General Regression Neural Networks written by Mark T. Leung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Predicting currency movements has always been a problematic task as most conventional econometric models are not able to forecast exchange rates with significantly higher accuracy than a naive random walk model. For large multinational firms which conduct substantial currency transfers in the course of business, being able to accurately forecast the movements of exchange rates can result in considerable improvement in the overall profitability of the firm. In this study, we apply the General Regression Neural Network (GRNN) to predict the monthly exchange rates of three currencies, British pound, Canadian dollar, and Japanese yen. Our empirical experiment shows that the performance of GRNN is better than other neural network and econometric techniques included in this study. The results demonstrate the predictive strength of GRNN and its potential for solving financial forecasting problems.
Forecasting Exchange Rates Using Feedforward And Recurrent Neural Networks
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Author : Chongming Guan
language : en
Publisher:
Release Date : 1994
Forecasting Exchange Rates Using Feedforward And Recurrent Neural Networks written by Chongming Guan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
An Application Of The Feedforward Neural Network Model In Currency Exchange Rate Forecasting
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Author : Julia X. Ye
language : en
Publisher:
Release Date : 1994
An Application Of The Feedforward Neural Network Model In Currency Exchange Rate Forecasting written by Julia X. Ye and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Foreign exchange rates categories.
Using Artificial Neural Networks For Timeseries Smoothing And Forecasting
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Author : Jaromír Vrbka
language : en
Publisher: Springer Nature
Release Date : 2021-09-04
Using Artificial Neural Networks For Timeseries Smoothing And Forecasting written by Jaromír Vrbka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-04 with Technology & Engineering categories.
The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets.
Regression Neural Network For Error Correction In Foreign Exchange Forecasting And Trading
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Author : An-Sing Chen
language : en
Publisher:
Release Date : 2006
Regression Neural Network For Error Correction In Foreign Exchange Forecasting And Trading written by An-Sing Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Predicting exchange rates has long been a concern in international finance as most standard econometric methods are unable to produce significantly better forecasts than the random walk model. Recent studies provide some evidence for the ability of using multivariate time series models to generate better forecasts. At the same time, artificial neural networks have been emerging as alternatives to predict exchange rates. In this paper, we propose an adaptive forecasting approach which combines the strengths of neural networks and multivariate econometric models. This hybrid approach contains two forecasting stages. In the first stage, a time series model generates estimates of the exchange rates. In the second stage, General Regression Neural Network is used to correct the errors of the estimates. A number of tests and statistical measures are then applied to compare the performances of the two-stage models (with error-correction by neural network) with those of the single-stage models (without error-correction by neural network). Both empirical and trading simulation experiments suggest that the proposed hybrid approach not only produces better exchange rate forecasts but also results in higher investment returns than the single-stage models. The effect of risk aversion in currency trading is also considered.
Forecasting Exchange Rates Using Feedforward And Recurrent Neural Networks
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Author : Chung-Ming Kuan
language : en
Publisher:
Release Date : 1993
Forecasting Exchange Rates Using Feedforward And Recurrent Neural Networks written by Chung-Ming Kuan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.